AI/ML Engineer (Generative AI, ML,AWS)

Infosys; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Infosys is seeking an experienced AI/ML Engineer with Generative AI expertise to design, develop, deploy, and optimize AI-driven solutions in a cloud-first environment. The role focuses on building scalable ML models, RAG-driven architectures, and responsible AI practices using AWS Bedrock/SageMaker.

The ideal candidate will have hands-on experience with LLMs, LangGraph, LangChain, and vector databases, with strong Python skills and experience deploying ML applications in production.

Qualifications

• MCA/MSc/MTech/BTech required or equivalent.
• Hands-on experience with Generative AI and large language models (LLMs).
• Experience deploying AI/ML solutions in production environments.

Responsibilities

• Design/deploy ML pipelines and LLM-powered agents (RAG, Agentic AI) using AWS Bedrock, SageMaker, LangGraph.
• Develop, train, and productionize ML models (churn, recommendation, forecasting) with MLOps practices.
• Build RAG architectures, integrate LLM APIs, prompt engineering, and responsible AI guardrails.
• Strong Python and ML libraries; hands-on SageMaker; vector DBs like FAISS/Pinecone/OpenSearch.

Skills

Python

ML libraries (Pandas, NumPy, scikit-le

Generative AI/LLMs

Prompt engineering

RAG architectures

LangChain/LangGraph

AWS Bedrock/SageMaker

REST APIs/microservices

Git/CI/CD

Education

MCA/MSc/MTech/BTech

Tools

AWS Bedrock

SageMaker

LangGraph

LangChain

FAISS

Pinecone

OpenSearch

Git

CI/CD

Job description

Job DescriptionWe are seeking an experienced AI/ML Engineer with expertise in Generative AI, Machine Learning, and AWS Cloud to design, develop, deploy, and optimize AI-driven solutions. The ideal candidate should have hands‑on experience in building scalable ML models, implementing GenAI use cases using LLMs, and deploying AI applications on AWS.

Roles & Responsibilities

• Design/deploy ML pipelines and LLM-powered agents (RAG, Agentic AI) using AWS Bedrock, SageMaker, LangGraph
• Develop, train, and productionize ML models (churn, recommendation, forecasting) with MLOps practices
• Build RAG architectures, integrate LLM APIs, prompt engineering, and responsible AI guardrails
• Strong Python (Scikit-learn, TensorFlow, PyTorch); hands‑on SageMaker; vector DBs (FAISS, Pinecone, OpenSearch)
• Must-have: Python, LangGraph/LangChain, Bedrock/OpenAI integration | Nice-to-have: LLM fine‑tuning, LangSmith/W&B, AWS ML Specialty

Technical Requirement

Strong proficiency in Python and AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
Hands‑on experience with Generative AI and Large Language Models (LLMs).
Experience with OpenAI, Claude, Gemini, Llama, or similar foundation models.
Strong understanding of Prompt Engineering, RAG, Embeddings, and Vector Databases.
Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
Hands‑on experience with AWS Services such as:
SageMaker
Bedrock
Lambda
EC2
S3
Glue
API Gateway
CloudWatch
Strong SQL and data processing skills.
Experience with REST APIs and microservices architecture.
Knowledge of Git, CI/CD, and Agile methodologies.

Educational Requirement

MCA,MSc,MTech,BTech

Preferred Skills

Technology->AI-Data science->Machine Learning,Technology->AI-Generative AI->Generative AI for Data Analytics,Technology->AI-Data science->PYTHON

Service Line

Data & Analytics Unit